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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

2D kinetic-ion simulations of inverted corona fusion targets

Laser-driven “inverted corona” fusion targets have attracted interest as a low-convergence neutron source and platform for studying kinetic physics. The scheme consists of a hollow or gas-filled spherical shell made of deuterated plastic. The shell has one or more laser entrance holes (LEH), resembling a spherical hohlraum. The laser passes through the LEH’s and illuminates the interior surface of the shell, ablating a plasma that travels inward towards the target center. Long ion mean free paths in the converging plasma can lead to significant interpenetration, atomic mix, and other kinetic effects. Here, in this work we report on numerical simulations of inverted corona targets using the kinetic-ion, fluid–electron hybrid particle-in-cell (PIC) approach in 2D RZ geometry. 2D simulations suggest that shape effects do not have a significant impact on plasma evolution and observed yield trends are primarily the result of 1D kinetic mix mechanisms. Simulations are also compared against available experimental data recorded at the OMEGA laser facility. In particular, synthetic x-ray emission images show good qualitative agreement with experimental results, albeit with an apparent timing discrepancy for the two-sided vacuum target. More generally, we demonstrate the potential of hybrid-PIC simulations for full-system modeling and experimental design, including collisional absorption of laser energy, plasma evolution, mix, and fusion burn.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Coarse-Grained Simulations of Polyrotaxane Hydrogels under Quiescent and Shear Conditions

Cyclodextrin-based polyrotaxanes (PR) form hydrogels in water through cyclodextrin (CD) aggregation and crystallization. These networks can break under shear flows, making them versatile platforms for extrusion-based 3D printing. To optimize the material properties of 3D-printed PR gels, a microscopic understanding of the structural evolution during 3D printing is necessary. Here, we employ coarse-grained (CG) simulations to reveal the PR assembly process at the molecular level. Our simulations reproduce the experimental crystal morphologies of PR at varying concentrations and chain lengths under quiescent conditions. Using nonequilibrium simulations, we show shear flow ruptures crystalline domain connectivity in PR gels and stacks the lamellae in the gradient direction, allowing the materials to flow during 3D printing. After the cessation of flow, the anisotropic crystal alignment and absence of available dangling PR diminish the intercrystal connectivity. The printed materials are therefore mechanically weaker than the pristine hydrogels, in agreement with experimental results. Nonetheless, by relating the microscopic structural evolution with viscoelastic properties of PR gels and solutions, we elucidate how flow conditions and sample composition affect the 3D printing performance of PR hydrogels.

Smith, Cameron D. [Dartmouth College, Hanover, NH ↗
DOE OSTI2025

Dichotomous Temperature Response in the Electronic Structure of Epitaxially Grown Altermagnet MnTe

The altermagnet candidate MnTe has recently gained significant interest due to its unconventional magnetic ordering. One of the key features of altermagnetism is the momentum-dependent spin-split band and its temperaturedependent evolution. Yet a fully momentum-resolved experimental investigation, including out-of-plane direction, is still lacking. Here, we systematically investigate the electronic structure of epitaxially grown MnTe by using angle-resolved photoemission spectroscopy (ARPES). Our photon-energy-dependent ARPES data reveal significant out-of-plane dispersions consistent with previous theoretical calculations. More interestingly, we identify two distinct temperature-dependent electronic band structure evolutions at different out-of-plane momentum positions: momentum-dependent energy shifts at the nodal plane and substantial spectral weight suppression at the off-nodal plane. These findings may suggest the importance of considering both the itinerant and localized nature of the magnetic ordering and momentum-dependent interactions. Our work provides crucial insights into the complex correlation between momentum, temperature, and electronic structure in MnTe, contributing to a deeper understanding of altermagnetism.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Iron isotope fractionation between solid and liquid metal in the Fe-P±Ni system: Experimental constraints and implications for meteorites

Iron meteorites record a range of Fe isotope compositions that hold valuable information regarding the evolution of their parent bodies. Interpreting this isotopic variability, however, requires experimental constraints on the equilibrium isotope fractionation between phases. It is thought that the cores of many iron meteorite parent bodies experienced fractional crystallization, during which crystallization of solid iron-nickel occurs from an increasingly non-metal-rich liquid alloy. Phosphorus is one component of this alloy, and this study provides the first constraints on Fe-isotope fractionation between solid and liquid alloys in the Fe-Ni-P system. Experiments comprising Fe and P show a clear enrichment in the light isotopes of Fe in the liquid phase, which increases with the amount of phosphorus. Nickel-bearing samples are offset from the trend defined by Ni-free experiments, which is accounted for by the change in the solid alloy phase from a body-centered cubic to face-centered cubic structure upon the addition of Ni. The increasing light isotope enrichment of the liquid with increasing P content suggests interstitial solution of P, which is known to lengthen Fe-Fe bonds in Fe-P liquids (Waseda and Shiraishi 1977). Results suggest a negligible effect of P on Fe isotope fractionation during planetesimal core crystallization. Iron isotopes may, however, prove useful for identifying the petrogenesis of schreibersite in pallasites and iron meteorites.

58 GEOSCIENCES↗
DOE OSTI2025

Reaching the prolate-oblate boundary at 𝑁=116 via first fragmentation of a 198 Pt beam: Sharp transition to triaxiality in 189 Ta

High-spin isomers in very-neutron-rich 𝐴≈190 Hf-Ta-W nuclei were populated via the pioneering fragmentation of a 198 Pt primary beam at the National Superconducting Cyclotron Laboratory. The nuclei were implanted in a Si detector stack surrounded by the Gamma-Ray Energy Tracking In-beam Nuclear Array (GRETINA) to detect delayed 𝛾 rays, providing first level schemes using 𝛾−𝛾 coincidence data from isomeric decays in this previously inaccessible region of the nuclear chart. Here, a sudden transition to a strong triaxial shape is observed in the very-neutron-rich 189 Ta (𝑁 = 116) nucleus from axially prolate shapes in lighter Ta isotopes, providing a critical experimental benchmark for competing theoretical predictions of nuclear-shape evolution.

150 ≤ A ≤ 189↗
DOE OSTI2025

Assessment of metadynamic recrystallization in single copper particle impacts by focused ion beam tomography

We study single Cu-on-Cu impacts relevant to cold spray deposition and quantitatively analyze the metadynamic recrystallization (mDRX) that takes place after the impact by virtue of lingering impact adiabatic heat. Unlike prior studies, the current full 3D tomographic analysis of the mDRX volume shows that mDRX is extremely common in such impacts, although it is often missed when examining 2D sections. We also report an unexpected trend: there is a “sour spot” for mDRX at velocities about 20–40 % above the velocity for particle adhesion. This non-monotonic trend is contrary to the expectations based on increasing adiabatic heating with velocity. With a schematic model, we show that the trend can be explained on the basis of heat transfer: cooling of the heat-affected region is limited by transport through the bonded regions at the particle-substrate interface. Thus, bonding has a prominent role in the heat dissipation process and the best bonded particles most rapidly bulk quench, avoiding mDRX. Here, the developed semi-empirical model aligns with the experimental findings and may help inform microstructural evolution during cold spray and post-spray processing.

FIB-SEM tomography↗
DOE OSTI2024

An introduction to Spent Nuclear Fuel decay heat for Light Water Reactors: a review from the NEA WPNCS

This paper summarized the efforts performed to understand decay heat estimation from existing spent nuclear fuel (SNF), under the auspices of the Working Party on Nuclear Criticality Safety (WPNCS) of the OECD Nuclear Energy Agency. Needs for precise estimations are related to safety, cost, and optimization of SNF handling, storage, and repository. The physical origins of decay heat (a more correct denomination would be decay power) are then introduced, to identify its main contributors (fission products and actinides) and time-dependent evolution. Due to limited absolute prediction capabilities, experimental information is crucial; measurement facilities and methods are then presented, highlighting both their relevance and our need for maintaining the unique current full-scale facility and developing new ones. The third part of this report is dedicated to the computational aspect of the decay heat estimation: calculation methods, codes, and validation. Different approaches and implementations currently exist for these three aspects, directly impacting our capabilities to predict decay heat and to inform decision-makers. Finally, recommendations from the expert community are proposed, potentially guiding future experimental and computational developments. One of the most important outcomes of this work is the consensus among participants on the need to reduce biases and uncertainties for the estimated SNF decay heat. If it is agreed that uncertainties (being one standard deviation) are on average small (less than a few percent), they still substantially impact various applications when one needs to consider up to three standard deviations, thus covering more than 95% of cases. The second main finding is the need of new decay heat measurements and validation for cases corresponding to more modern fuel characteristics: higher initial enrichment, higher average burnup, as well as shorter and longer cooling time. Similar needs exist for fuel types without public experimental data, such as MOX, VVER, or CANDU fuels. A third outcome is related to SNF assemblies for which no direct validation can be performed, representing the vast majority of cases (due to the large number of SNF assemblies currently stored, or too short or too long cooling periods of interest). A few solutions are possible, depending on the application. For the final repository, systematic measurements of quantities related to decay heat can be performed, such as neutron or gamma emission. This would provide indications of the SNF decay heat at the time of encapsulation. For other applications (short- or long-term cooling), the community would benefit from applying consistent and accepted recommendations on calculation methods, for both decay heat and uncertainties. This would improve the understanding of the results and make comparisons easier.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Dynamic in-context learning with conversational models for data extraction and materials property prediction

The advent of natural language processing and large language models (LLMs) has revolutionized the extraction of data from unstructured scholarly papers. However, ensuring data trustworthiness remains a significant challenge. In this paper, we introduce PropertyExtractor, an open-source tool that leverages advanced conversational LLMs such as Google gemini-pro and OpenAI gpt-4, blends zero-shot with few-shot in-context learning, and employs engineered prompts for the dynamic refinement of structured information hierarchies—enabling autonomous, efficient, scalable, and accurate identification, extraction, and verification of material property data. Our tests on material data demonstrate precision and recall that exceed 95% with an error rate of ∼9%, highlighting the effectiveness and versatility of the toolkit. Finally, databases for 2D material thicknesses, a critical parameter for device integration, and energy bandgap values are developed using PropertyExtractor. In particular, for the thickness database, the rapid evolution of the field has outpaced both experimental measurements and computational methods, creating a significant data gap. Our work addresses this gap and showcases the potential of PropertyExtractor as a reliable and efficient tool for the autonomous generation of various material property databases, advancing the field.

Ekuma, Chinedu E. (ORCID:0000000258527556)↗
DOE OSTI2024

METHOD FOR EXPOSING IRRADIATED FUEL CLADDING TO RAPID THERMAL TRANSIENTS

Reactor core materials exposed to rapid thermal transients during accidents can experience significant changes in mechanical properties as irradiation hardness is recovered. Understanding material performance during transients using computer modeling requires accurate descriptions of mechanical property evolution with time and temperature. A simple experimental capability was developed to expose irradiated Zircaloy to a simulated thermal transient using immersion in molten tin (at 675°C) to rapidly heat and hold before rapidly cooling with a water quench. Multiple heating-cooling cycles using a nonirradiated tensile specimen showed simplicity and viability. Based on preliminary test results, a robust system was established for routine evaluation of simulated thermal accident scenarios in the Low Activation Materials Design and Analysis (LAMDA) laboratory at Oak Ridge National Laboratory (ORNL). This paper summarizes system development and nonirradiated Zircaloy commissioning test results. Future experiments will conduct tensile tests on irradiated Zircaloy after various rapid temperature profiles.

Byun, TS↗
DOE OSTI2025

Mesoscale Modeling of Dislocation Cell Structure Evolution and Radiation-Induced Segregation in Additively Manufactured Austenitic Stainless Steel

Structural alloys under irradiation develop radiation-induced segregation (RIS) at point defect sinks, which lead to undesired changes in the alloy's properties. Additively manufactured austenitic stainless steels are expected to yield a distinct response to irradiation damage owing to their unique as-printed dislocation cell structure. In this talk, we present the development of a mesoscale model for dislocation cell structure evolution coupled with RIS using the MOOSE framework. The evolution of network dislocations within spatially distinct cells and cell walls are modeled using climb-mediated edge annihilation and generation processes. Starting with initial microstructures of as-printed non-equilibrium segregations at dislocation cell walls, our 2D and 3D simulations explore the effects of irradiation temperature, dose rate, dislocation sink bias, and specimen thickness on microstructure evolution. The results will be compared against experimental characterizations of in-situ and ex-situ ion-irradiated samples, and the implications of evolving cell structure on irradiation damage response will be discussed.

additive manufacturing↗
DOE OSTI2026

Evolution of Electronic Properties of Graphene Nanoribbons with Progressive Carving: From Straight to Porous to Chevron Ribbons

Graphene nanoribbons (GNRs) are highly versatile materials due to their unique electronic, magnetic, and optical properties, which can be precisely tuned by controlling their width, edge structure, and topology. Here, we report the on-surface synthesis and characterization of a straight N = 15 armchair GNR with periodic annulene nanopores (15-pGNR). It serves as a structural link between two well-established GNRs: the pristine N = 15 armchair GNR without pores (15-AGNR) and the chevron GNR (cGNR). With the addition of the 15-pGNR reported in this study, these three GNRs form a rare experimentally accessible series of ribbons, in which the evolution of electronic properties can be tracked upon progressive carving of a basic 15-AGNR: first, by creating periodic nanopores to form 15-pGNR and then by extending the pore area and producing meandering cGNR. We have designed a molecular precursor for the 15-pGNR and grown the nanoribbons on single-crystal gold substrates by on-surface synthesis in ultra-high vacuum (UHV) conditions. The atomically precise structure of 15-pGNR was confirmed by scanning tunneling microscopy (STM) and non-contact atomic force microscopy (nc-AFM). The band gap of 15-pGNR was studied by scanning tunneling spectroscopy (STS) and dI/dV mapping, and the occupied electronic levels were investigated by angle-resolved photoemission spectroscopy (ARPES). A theoretical and experimental comparison of 15-pGNRs, 15-AGNRs, and cGNRs demonstrates that the introduction of periodic nanopores into 15-AGNR leads to a more than 2-fold increase in its band gap. In contrast, the band gaps of 15-pGNR and cGNR differ only by about 15%. Such band gap increase can be qualitatively understood to arise from two combined effects, the periodic perforation of the graphene lattice and the confinement effect induced by the GNR width.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Phase-field modeling of stored-energy-driven grain growth with intra-granular variation in dislocation density

Abstract We present a phase-field (PF) model to simulate the microstructure evolution occurring in polycrystalline materials with a variation in the intra-granular dislocation density. The model accounts for two mechanisms that lead to the grain boundary migration: the driving force due to capillarity and that due to the stored energy arising from a spatially varying dislocation density. In addition to the order parameters that distinguish regions occupied by different grains, we introduce dislocation density fields that describe spatial variation of the dislocation density. We assume that the dislocation density decays as a function of the distance the grain boundary has migrated. To demonstrate and parameterize the model, we simulate microstructure evolution in two dimensions, for which the initial microstructure is based on real-time experimental data. Additionally, we applied the model to study the effect of a cyclic heat treatment (CHT) on the microstructure evolution. Specifically, we simulated stored-energy-driven grain growth during three thermal cycles, as well as grain growth without stored energy that serves as a baseline for comparison. We showed that the microstructure evolution proceeded much faster when the stored energy was considered. A non-self-similar evolution was observed in this case, while a nearly self-similar evolution was found when the microstructure evolution is driven solely by capillarity. These results suggest a possible mechanism for the initiation of abnormal grain growth during CHT. Finally, we demonstrate an integrated experimental-computational workflow that utilizes the experimental measurements to inform the PF model and its parameterization, which provides a foundation for the development of future simulation tools capable of quantitative prediction of microstructure evolution during non-isothermal heat treatment.

Materials Science↗
DOE OSTI2024

Photon-triggered jets as probes of multi-stage jet modification

Prompt photons are created in the early stages of heavy ion collisions and traverse the QGP medium without any interaction. Therefore, photontriggered jets can be used to study the jet quenching in the QGP medium. In this work, photon-triggered jets are studied through different jet and jet substructure observables for different collision systems and energies using the JETSCAPE framework. Since the multistage evolution used in the JETSCAPE framework is adequate to describe a wide range of experimental observables simultaneously using the same parameter tune, we use the same parameters tuned for jet and leading hadron studies. The same isolation criteria used in the experimental analysis are used to identify prompt photons for better comparison. For the first time, high-accuracy JETSCAPE results are compared with multi-energy LHC and RHIC measurements to better understand the deviations observed in prior studies. This study highlights the importance of multistage evolution for the simultaneous description of experimental observables through different collision systems and energies using a single parameter tune.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Modeling resistive-inductive evolution of currents in Wendelstein 7-X

This research investigates the temporal evolution of the toroidal plasma current in the Wendelstein 7-X (W7-X) stellarator under different heating, fueling, and current drive scenarios. The THRIFT code has been modernized and its predictions of the evolution of the toroidal current have been compared against experimentally measured currents in W7-X. Good agreement is found with respect to the characteristic timescale between experimentally measured and simulated toroidal currents. The total bootstrap current is under-predicted owing to the applicability of the BOOTSJ model for the plasma collisionalities in question. Edge plasma resistivity is found to play an important role in the asymptotic behavior of the evolution of the current, indicating a possible limitation of the minimum plasma temperature when applying this model. Simulations of ECCD and heating power steps show THRIFT is capable of capturing the dynamical evolution of the current in response to changes in current sources. Future uses of THRIFT include validating and benchmarking other non-inductive current models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Polarization-driven band topology evolution in twisted MoTe 2 and WSe 2

Motivated by recent experimental observations of opposite Chern numbers in R-type twisted MoTe 2 and WSe 2 homobilayers, we perform large-scale density-functional-theory calculations with machine learning force fields to investigate moiré band topology across a range of twist angles in both materials. We find that the Chern numbers of the moiré frontier bands change sign as a function of twist angle, and this change is driven by the competition between moiré ferroelectricity and piezoelectricity. Our large-scale calculations, enabled by machine learning methods, reveal crucial insights into interactions across different scales in twisted bilayer systems. The interplay between atomic-level relaxation effects and moiré-scale electrostatic potential variation opens new avenues for the design of intertwined topological and correlated states, including the possibility of mimicking higher Landau level physics in the absence of magnetic field.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Design and Synthesis of PtPdNiCoMn High‐Entropy Alloy Electrocatalyst for Enhanced Alkaline Hydrogen Evolution Reaction: A Theoretically Supported Predictive Design Approach

Electrocatalytic hydrogen generation requires a multifunctional electrocatalyst with abundant active sites to drive multielectron transfer reactions. High entropy alloys (HEA) are five or more-elements with high configurational entropy are considered unique materials for next-generation electrocatalysts. Here, in this work, based on new screening guidelines for catalyst selections that combine density-functional theory calculated Gibbs formation-enthalpy with bond length and electronegativity variance, a novel HEA electrocatalyst consisting of five elements, namely, Pt, Pd, Ni, Co, and Mn has been designed. By simple room temperature electrodeposition, the designed catalyst is prepared and its hydrogen evolution reaction (HER) is explored and validated through experimental and theoretical approaches. The HEA demonstrated a superior HER activity with an overpotential of 22.6 mV at -10 mA cm -2 which outperforms Pt/C commercial catalyst. No evident degradation of the material is detected even after 100 hours of continuous operation under high current density. Moreover, the HEA has shown exceptional performance in harsh electrolyte conditions such as in simulated seawater and actual seawater. Remarkably, the density-functional theory calculated Gibbs formation-enthalpy is small (≈0 eV) compared to Pt/C placing the new HEA near the apex of Trasatti's model of Volcano plot, which is also suggestive of superior HER activity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A single-zone zero-dimensional study of HCCI combustion of methanol dehydration products to enable ignition of direct-injected methanol

Methanol is an alternative fuel gaining traction in the maritime sector. Its direct adoption, however, is accompanied by a unique set of technical challenges, such as low cetane number and high latent heat of vaporization. An approach to overcome these challenges is being developed at the US Department of Energy’s Oak Ridge National Laboratory, where onboard generation of dimethyl ether (DME) via catalytic dehydration of methanol can be used to assist in the mixing controlled combustion of direct-injected (DI) methanol. The generated mixture from this dehydration process can be premixed with intake air to condition the cylinder via. homogeneous charge compression ignition (HCCI) for subsequent DI methanol. In this preliminary work, various catalyst or reactor conversion efficiencies were simulated (using bottles) at constant DME and water flow at low load on a single-cylinder marine-variant of a CAT® C18 18 L engine with a 145 mm bore. To substantiate the experimental findings, a zero-dimensional engine model was developed in Cantera using a DME mechanism with 79 species and 658 reactions. Results presented include experimental and simulation heat release rate comparisons, species evolution information, and constant volume ignition delay (ID) for DI methanol with and without background species from HCCI of the premixed products from different reactor efficiencies. The results suggest that thermal effects dominate the DI methanol ignition process, and this work provides a chemical kinetic foundation or guideline for developing future control schemes.

Tyrewala, Daanish [ORNL] (ORCID:0000000208599324)↗
DOE OSTI2025

Active Learning Surrogates for Integrating Electron Microscopy and Computational Insights from Simulations in Autonomous Experiments

Artificial Intelligence (AI) combined with simulations and experiments has great potential to accelerate scientific discovery across technology and pharmaceuticals. However, the gap between simulations and experiments is challenging due to disparities in time and scale, making it difficult to estimate properties like energy and electronic states from experiments, and to provide feedback based on theoretical insights.Our research addresses the challenge by developing unique deep kernel based surrogate models that learns from microscopic images, mapping structural features to energy differences from defect formation. We start with full-training using simulated images to determine optimal settings, establishing a baseline for active learning. Using these settings from the baseline, active learning is trained, and predicts structures along simulation trajectories based on uncertainty and energetic stability, thus reducing data requirements, simulation time and computational costs. The results demonstrate that the model achieves a low average error margin of approximately 0.03 meV, indicating good performance. To enhance feature extraction and reconstruction capabilities, we developed an autoencoder-decoder as additional surrogate to create latent space to capture essential features, enabling precise comparisons between simulations and experiments. The results from this model achieved a reconstruction loss of around 0.2 and accurately reconstructed molecular structures.Overall, this work advances the steering of experiments through computational simulations by employing a surrogate models that actively predicts the trajectories of structural evolution, achieving time-to-solution comparable to experimental measurements.

Saranathan, Gayathri [Hewlett-Packard]↗